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https://github.com/e-kotov/2024-30daymapchallenge


https://github.com/e-kotov/2024-30daymapchallenge

30daymapchallenge maps reproducible

Last synced: about 1 month ago
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README 

        



# 2024 \#30DayMapChallenge



# 1. Points



**Dominance of Female Commuters in Urban Destinations Across Spain**



![Dominance of Female Commuters in Urban Destinations Across

Spain](maps/01-points.svg)



To recreate the plot, use the

[`{spanishoddata}`](https://ropenspain.github.io/spanishoddata/) R

package and the [R/01-points.R](R/01-points.R) script in this

repository.



See threads on

[LinkedIn](https://www.linkedin.com/posts/egorkotov_30daymapchallenge-points-rstats-activity-7258040088348053504-gEX9),

[Mastodon](https://datasci.social/@EgorKotov/113406894220654694),

[Bluesky](https://bsky.app/profile/egorkotov.bsky.social/post/3l7tvg2nzlq2w),

[Twitter/X](https://x.com/EgorKotov/status/1852274386298167504).



# 2. Lines



**Gradual Recovery of Road Connectivity after the Passage of (storm)

DANA in Spain**



*In solidarity with the victims and their families.*



Affected road segments may be shorter. Check the exact kilometer

intervals at https://www.dgt.es/.



Credits to Virgilio Gómez-Rubio

([@precariobecario](https://x.com/precariobecario)) and Mireia Camacho

([@mireiacamacho75](https://x.com/mireiacamacho75)) for pointing me to

the data and

[capturing](https://github.com/DataMirai/ShinyCarreterasInundaciones/blob/main/carreteras_cortadas.csv)

the affected roads as of October 31.



![Gradual Recovery of Road Connectivity after the Passage of DANA

(storm) in Spain](maps/02-lines.png)



To recreate the plot, use the [R/02-lines.R](R/02-lines.R) script in

this repository.



See threads on

[LinkedIn](https://www.linkedin.com/posts/egorkotov_30daymapchallenge-lines-roads-activity-7258387373883801600-xX3d),

[Mastodon](https://datasci.social/@EgorKotov/113412609537680635),

[Bluesky](https://bsky.app/profile/egorkotov.bsky.social/post/3l7xdzgeher2d),

[Twitter/X](https://x.com/EgorKotov/status/1852639535668359633).



# 3. Polygons



**Up to 2% of typical daily mobility in Spain was affected by (storm)

DANA**



The map shows the affected municipalities in Spain and emphasizes the

most affected areas by exaggerating the size of the polygons by the

number of trips.



*In solidarity with the victims and their families.*



Based on road incidents data by  and open mobility

data by

[https://www.transportes.gob.es/](https://www.transportes.gob.es/ministerio/proyectos-singulares/estudios-de-movilidad-con-big-data/opendata-movilidad).



![Up to 2% of typical daily mobility in Spain was affected by (storm)

DANA](maps/03-polygons.svg)



See threads on

[LinkedIn](https://www.linkedin.com/posts/egorkotov_30daymapchallenge-polygons-spain-activity-7258857807637004288-H9ww),

[Mastodon](https://datasci.social/@EgorKotov/113419659708438464),

[Bluesky](https://bsky.app/profile/egorkotov.bsky.social/post/3la2ie6nyoa2r),

[Twitter/X](https://x.com/EgorKotov/status/1853091018725302381).



# 4. Hexagons



*skipped for now*



# 5. A Journey



All journeys in Spain in one day.



https://github.com/user-attachments/assets/a939b9d2-c685-4321-b617-abff87f89213



See threads on

[LinkedIn](https://www.linkedin.com/posts/egorkotov_30daymapchallenge-journey-activity-7259507774324195328-Dnxx),

[Mastodon](https://datasci.social/@EgorKotov/113432261713732931),

[Bluesky](https://bsky.app/profile/egorkotov.bsky.social/post/3laa3h4fr5e2z),

[Twitter/X](https://x.com/EgorKotov/status/1853726331038540163).



# 9. AI Only



ChatGPT/DALL-E was given a map of Spain (to memorise the locations of

cities) and asked to generate a new map with human mobility flows.



![AI Only](maps/09-ai-only.jpg)



See threads on

[LinkedIn](https://www.linkedin.com/posts/egorkotov_30daymapchallenge-aiabronly-humanmobility-activity-7261050165346668545-1dZm),

[Mastodon](https://datasci.social/@EgorKotov/113453863690205418),

[Bluesky](https://bsky.app/profile/egorkotov.bsky.social/post/3lajocu6eu223),

[Twitter/X](https://x.com/EgorKotov/status/1855280788847181909).



# 10. Pen and Paper



Hand drawn logo of `{spanishoddata}` R package. Get it here:

https://github.com/rOpenSpain/spanishoddata/



![Hand drawn logo of `{spanishoddata}` R

package](maps/10-pen-and-paper.jpg)



See threads on

[LinkedIn](https://www.linkedin.com/posts/egorkotov_30daymapchallenge-penandpaper-rstats-activity-7261377898064883713-WOMS),

[Mastodon](https://datasci.social/@EgorKotov/113459011680094552),

[Bluesky](https://bsky.app/profile/egorkotov.bsky.social/post/3lalxovcaxk2i),

[Twitter/X](https://x.com/EgorKotov/status/1855611133941436661).



# 12. Time and Space



![Impact of DANA on mobility in a neighbourhood in

Valencia](maps/12-time-and-space.png)



See threads on

[LinkedIn](https://www.linkedin.com/posts/egorkotov_30daymapchallenge-timeandspace-dana-activity-7262140965237215233-gvf4),

[Mastodon](https://datasci.social/@EgorKotov/113470963311439758),

[Bluesky](https://bsky.app/profile/egorkotov.bsky.social/post/3larbjwx4h22g),

[Twitter/X](https://x.com/EgorKotov/status/1856377020919197754).